Custom Prediction Routine on Google AI Platform from Coursera

Please note: You will need a Google Cloud Platform account to complete this course. Your GCP account will be charged as per your usage. Please make sure that you are able to access Google AI Platform within your GCP account. You should be familiar with python programming, and Google Cloud Platform before starting this hands on project. Please also ensure that you have access to the custom prediction routine feature in Google AI Platform.

In this 2-hour long project-based course, you will learn how to deploy, and use a model on Google’s AI Platform. Normally, any model trained with the TensorFlow framework is quite easy to deploy, and you can simply upload a Saved Model on Google Storage, and create an AI Platform model with it. But, in practice, we may not always use TensorFlow. Fortunately, the AI Platform allows for custom prediction routines as well and that’s what we are going to focus on. Instead of converting a Keras model to a TensorFlow Saved Model, we will use the h5 ﬁle as is. Additionally, since we will be working with image data, we will use this opportunity to look at encoding and decoding of byte data into string for data transmission and then encoding of the received data in our custom prediction routine on the AI Platform before using it with our model.

This course runs on Coursera's hands-on project platform called Rhyme. On Rhyme, you do projects in a hands-on manner in your browser. You will get instant access to pre-configured cloud desktops containing all of the software and data you need for the project. Everything is already set up directly in your Internet browser so you can just focus on learning. For this project, you’ll get instant access to a cloud desktop with (e.g. Python, Jupyter, and Tensorflow) pre-installed.

Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

What's inside

Syllabus

Custom Prediction Routine on Google AI Platform

In this 2-hour long project-based course, you will learn how to deploy and use a model on Google’s AI Platform. AI Platform allows for custom prediction routines in addition to TensorFlow, XGBoost and Sci-kit models, and that’s what we are going to focus on. Instead of converting a Keras model to a TensorFlow Saved Model, we will use the h5 ﬁle as is.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Teaches data formatting techniques for handling byte data

Builds a foundation in using custom prediction routines on Google AI Platform

Provides interactive hands-on practice with pre-configured desktops

Ideally suited for those with familiarity in Python programming and Google Cloud Platform

Reviews summary

Highly rated google ai course: custom prediction routine

Learners largely positive about this course, which teach them key concepts for building custom prediction models on Google AI Platform. Excellent content, good deployment training, and engaging assignments are all noted as key features of this course. The course has well received instructors and some learners note they got help quickly when they had questions. A few learners, though, indicate that the material may be outdated.

Learners satisfied with deployment training.

"Good course mainly for deployment purposes."

"Custom Prediction Routine on Google AI Platform"

Learners satisfied with instructor.

"Thank you Amit Yadav sir thank you for make me understand a very good way and thank you Coursera forgiving platform."

"I am Helpfull this corse"

Content was excellent and useful to learners.

"Content is very useful to the Students."

"Excellent content"

"The course "Custom Prediction Routine on Google A I Platform" is explained very well."

Some learners report material may be outdated.

"The VDO files are not like what I see on the current GCP."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Custom Prediction Routine on Google AI Platform with these activities:

Read 'Hands-On Machine Learning with TensorFlow 2.0' by Aurélien Géron

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Gain a comprehensive understanding of machine learning concepts and techniques by reading a foundational book in the field.

View Hands-On Machine Learning with Scikit-Learn,... on Amazon

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Acquire a copy of the book.
Read and study the book thoroughly.
Complete the exercises and assignments in the book.

Mentor junior data scientists or students interested in AI Platform

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Reinforce your knowledge by sharing it with others and fostering their growth in the field.

Browse courses on AI Platform

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Identify individuals who could benefit from your guidance.
Provide regular support and guidance.
Share resources and best practices.

Attend a workshop on advanced topics in AI Platform

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Supplement your learning by attending a workshop led by experts in the field.

Browse courses on AI Platform

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Identify and register for a relevant workshop.
Attend the workshop and actively participate.
Apply what you learn to your own projects.

Five other activities

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Practice using custom prediction routines on Google AI Platform

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Reinforce your understanding of custom prediction routines and their use on Google AI Platform by completing practice exercises.

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Set up your Google Cloud Platform account and enable AI Platform.
Create a custom prediction routine using Python.
Deploy your custom prediction routine to AI Platform.
Test your custom prediction routine with sample data.

Write a blog post explaining how to use custom prediction routines on Google AI Platform

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Enhance your understanding of custom prediction routines and improve your communication skills by creating a blog post that shares your knowledge with others.

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Research and gather information on custom prediction routines and AI Platform.
Write the blog post, including clear explanations and examples.
Format and publish your blog post.

Complete online tutorials on advanced topics related to AI Platform

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Expand your knowledge and skills by exploring advanced topics related to AI Platform through online tutorials.

Browse courses on AI Platform

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Identify specific areas where you want to enhance your knowledge.
Search for and select reputable online tutorials.
Follow the tutorials, completing exercises and assignments.

Develop a proof-of-concept project using AI Platform and custom prediction routines

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Solidify your understanding by building a practical project that incorporates the concepts of custom prediction routines on AI Platform.

Browse courses on AI Platform

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Define a problem or opportunity that can be addressed using AI Platform.
Design and implement a solution using custom prediction routines.
Test and refine your solution.
Present your project to others.

Participate in a hackathon or competition focused on AI Platform and machine learning

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Challenge yourself and gain valuable experience by participating in a competitive event.

Browse courses on AI Platform

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Identify and register for a relevant hackathon or competition.
Form a team or work individually.
Develop a solution that addresses the challenge.
Submit your solution and present it to judges.

Career center

Learners who complete Custom Prediction Routine on Google AI Platform will develop knowledge and skills that may be useful to these careers:

Machine Learning Engineer

Machine Learning Engineers develop and maintain the systems that make machine learning models possible. This course's lessons on using TensorFlow and building models for the AI Platform are essential knowledge that Machine Learning Engineers should be familiar with.

See salaries and explore the career path for Machine Learning Engineer

Data Scientist

Data Scientists use their expertise in machine learning and statistical modeling, like that taught in Custom Prediction Routine on Google AI Platform, to extract useful information from data. Apply to become a Data Scientist to make more informed decisions that drive the success of a company or organization.

See salaries and explore the career path for Data Scientist

Data Analyst

Data Analysts spend much of their time collecting and organizing data to be used in projects like model training. Custom Prediction Routine on Google AI Platform teaches skills in data preparation and transmission that would prove valuable in this role.

See salaries and explore the career path for Data Analyst

Software Engineer

Custom Prediction Routine on Google AI Platform teaches valuable skills in using Python and working with models, which would be valuable knowledge to Software Engineers looking to specialize in AI.

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Quantitative Analyst

Quantitative Analysts use mathematical and statistical models, such as those taught in Custom Prediction Routine on Google AI Platform, to make informed decisions in the financial sector.

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Financial Analyst

Companies and organizations seek out Financial Analysts to help inform their business decisions. Custom Prediction Routine on Google AI Platform teaches the handling and analysis of data, skills that are beneficial to a Financial Analyst.

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Business Analyst

Business Analysts gather and interpret data to gain insights into a range of business problems. This course helps develop skills in data analysis and modeling that could be applied in a Business Analyst role.

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Marketing Analyst

Custom Prediction Routine on Google AI Platform provides knowledge in model development, which can be applied to data analytics in marketing to help Marketing Analysts make data-driven decisions.

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Operations Research Analyst

Custom Prediction Routine on Google AI Platform provides training in building and using models for data, which can be leveraged by Operations Research Analysts when developing mathematical models.

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Risk Analyst

Custom Prediction Routine on Google AI Platform teaches skills in model building and data analysis, which Risk Analysts use to identify and assess risk.

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Statistician

Statisticians develop and use statistical models to analyze data. Custom Prediction Routine on Google AI Platform teaches foundational skills in working with models and data analysis, which would be helpful for Statisticians.

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Actuary

Actuaries use a variety of models and statistical methods in their work. This course teaches model building and data analysis, providing a helpful foundation for Actuaries.

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Market Researcher

Market Researchers study and analyze market trends to help businesses make informed decisions. Custom Prediction Routine on Google AI Platform provides training in data analysis and modeling, which can be useful for Market Researchers.

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Database Administrator

Custom Prediction Routine on Google AI Platform provides instruction on working with data in the cloud. Database Administrators often manage data and ensure its proper maintenance, and thus this course provides relevant knowledge.

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Data Engineer

Data Engineers build and maintain the infrastructure that allows for data analysis. The skills taught in Custom Prediction Routine on Google AI Platform, such as data preparation and model building, provide a solid foundation for becoming a Data Engineer.

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